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CohortNet: Empowering Cohort Discovery for Interpretable Healthcare Analytics

Summary: CohortNet auto-discovers interpretable patient cohorts by learning per-feature temporal embeddings, adaptively discretizing feature states via K-Means and exploring cohort patterns heuristically. Produces evidence-backed cohort representations for retrieval-driven, interpretable predictions with 2.8–4.1% AUC-PR gains. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13474
Venue
VLDB
Year
2024
Pagerank
4.1945683e-05
Overall Rank
11,034 | 23.24%
DOI
10.14778/3675034.3675041

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